Beyond the financial crisis: risk control and pricing methods
Satellite event of the 40th AIRO meeting (September 8-11, 2009)
The 2007-2008 credit crisis has witnessed an unprecedented deviation of market price dynamics from long term fair values posing new challenges to financial practitioners and the scientific community. The systemic extension of the crisis and the fall of equity and bonds markets provides on the other hand an ideal stress event to validate from a methodological viewpoint recent developments and new theoretical assumptions. The aim of this workshop is to bring together practicioners and scientists to discuss and present innovative approaches to deal with financial problems even in time of crisis.
14,30 – Leonardo Bellucci (MPS Capital services)
Beyond risk-neutral pricing, remaining fair (lesson from the crisis: the right price, not the true one)
The explosive innovation of derivative products has pushed quantitative finance away from its roots, firmly grounded in market analysis and trading activities. During the last decade, financial players have traded a vast range of exotic products, priced with models which, despite their ever increasing complexity and elegance, lack a solid foundation in the market mechanisms. The talk highlights this phenomenon in the case of the volatility smile, showing how different models produce very different results for exotic product prices and plain-vanilla hedge ratios. We propose a research program which offers a different (and in some ways more traditional) perspective on financial modeling, formulating the valuation problem in terms more faithful to its original meaning.
Leonardo Bellucci is currently Head of Staff Quants at MPS Capital Services. He obtained
a Ph.D. in Physics in 2002 at
15,00 – Alberto Bemporad (Università di Siena)
Stochastic receding horizon control for dynamic option hedging
Synthesizing complex financial securities requires an underlying portfolio of simpler securities that must be rebalanced dynamically to hedge the option writer against risk. In this talk I will present a dynamic hedging approach based on stochastic receding horizon control (also called stochastic model predictive control) by converting an (approximate) option pricing engine into an hedging engine that is applicable to a rather broad class of financial options. The resulting stochastic optimization problem is simply solved at each trading date as a least-squares problem with as many variables as the number of traded assets and as many constraints as the number of predicted scenarios. The approach is particularly useful and numerically viable for exotic options where closed-form results are not available, and for relatively long expiration dates where tree-based stochastic approaches are excessively complex.
Alberto Bemporad received the master degree in Electrical Engineering in 1993 and the Ph.D. in Control Engineering in 1997 from the University of Florence, Italy. He spent the academic year 1996/97 at the Center for Robotics and Automation, Dept. Systems Science & Mathematics, Washington University, St. Louis, as a visiting researcher. In 1997-1999, he held a postdoctoral position at the Automatic Control Lab, ETH, Zurich, Switzerland, where he collaborated as a senior researcher in 2000-2002. Since 1999 he is with the Faculty of Engineering of the University of Siena, Italy, where he is currently an associate professor. He has published about 200 papers in the area of hybrid systems, model predictive control, automotive control, multiparametric optimization, computational geometry, and robotics. He is coauthor of the Model Predictive Control Toolbox (The Mathworks, Inc.) and author of the Hybrid Toolbox for Matlab. He was an Associate Editor of the IEEE Transactions on Automatic Control during 2001-2004. He is Chair of the Technical Committee on Hybrid Systems of the IEEE Control Systems Society since 2002.
15,30 – Tommaso Gabbriellini (MPS Capital Services)
Inverse calibration method in derivatives pricing
Pricing an illiquid derivative security can be seen as the problem of synthesizing that security by means of a dynamic portfolio of liquid securities, which we refer to as hedge instruments. Such a portfolio is known as a replication strategy, and ultimately the price of the derivative security will be defined by the least costly of these strategies. In order for a pricing model to correctly determine a replication strategy, it must i) faithfully capture the statistical properties of the risk sources, ii) be able to reproduce the market prices of the hedge instruments, and iii) be compatible with the traders’ viewpoint on the dynamic evolution of the market prices. Calibrating a model in finance involves choosing its parameters in order to achieve the best possibile trade-off between these three objectives. In this presentation, after a brief introduction to basic concepts in quantitative finance, I will illustrate some typical problems that arise during the calibration of the Libor Market Model, the current standard in interest rate derivatives modeling.
Tommaso Gabbriellini graduated in Physics at the University of Florence and successively moved into the field of finance. He a took a master degree in Quantitative Finance at Bocconi University and immediately after started working at MPS Capital Services, his current employer, as a quantitative analyst. He works on the development and implementation of mathematical models for derivatives pricing.
16,00 - Coffee break
16,30 – Francesco Sandrini (Head of Institutional Investors - Pioneers Investments)
2008 volatility regime and efficient portfolio management
We propose to measure the value added by periodic portfolio rebalancing in actively managed strategies. Using Monte Carlo simulation and dynamic stochastic programming we simulate the pay off of an actively managed strategy. We seek to replicate this pay-off using a static investment based on the same Monte Carlo scenarios and investment timeframe, while including in the static portfolio a set of derivative strategies not available to the active manager. We claim that the allocation to the derivative strategies quantifies the value added by an active management and test the solution sensitivity to various input parameters. In particular we set the focus on understanding how the optimal hedging strategy changes in different market volatility (and correlation) regimes. We investigate data from the recent crisis and compare our solutions over different past market regimes.
17 – Pierluigi Riva (CEO of Operational Research Systems)
OR developments for efficient decision making in crisis periods
The credit crisis, the stock market downturn, and the economic slowdown have pushed credit spreads to historic highs and caused interest rates to fall sharply. This provides investors with extremely interesting opportunities, but also poses serious challenges in terms of optimal passive and active exposure to interest rate and credit risks.
Credit spreads are expected to narrow again but it is highly uncertain when and how this will take place. Economic stimulus packages will eventually result in increases in long term rates. Last but not least, the fundamental scarcity of natural resources and political pressure on central banks justify inflation fears for the medium to long term.
In these new market conditions, there is a clear and pressing need for investors and asset managers to better understand the tools that can be used to optimise investment in fixed-income products and manage associated risks. A robust integrated software environment for portfolio management and optimisation can host applications building up on applied experience of this kind in a natural and extendible fashion.
Pierluigi Riva made his studies in Economics, Econometrics and Operational Research at the University of Turin and at the London School of Economics. He has a long experience in developing applications in Finance, Energy and Industrial Environment. He is cofounder and president of Operational Research Systems, an Italian company with over a decade experience in building enterprise software systems based on the RAMS (Risk and Asset Management Studio) TM platform.
17,30 – Giorgio Consigli (Università di Bergamo) - joint work with Gaetano Iaquinta (Università di Bergamo), Patrizia Beraldi, Antonio Violi (Università della Calabria)
Simultaneous market and credit risk control on a generic corporate bond portfolio during the credit crisis
We present a multistage optimisation model that integrates two correlated risk sources, market and credit risk, under very general statistical assumptions and test the ability of the method to induce effective risk control strategies during the crisis period. Specifically the two key aspects of i) consistent risk factors statistical characterisation and ii) Effective dynamic optimization are analysed jointly and implemented, from a numerical viewpoint, in a scenario generator and a multistage stochastic programming model to yield an integrated decision tool with practical relevance.
Giorgio Consigli is currently associate professor of applied mathematics in economics and finance at the University of Bergamo and visiting professor of finance at the University of Svizzera Italiana in Lugano. He has been member of the Centre for Financial Research at the University of Cambridge between 1995 and 1997 and Head of quant research at UniCredit Banca Mobiliare, the investment bank of the UniCredit banking group, between 2000 and 2002. Since 2006 he is Director of FinMonitor a privately funded research centre on financial institutions at the University of Bergamo. In August 2007 he has been elected member of the International Committee on Stochastic Programming (COSP). He has an active research cooperation with the international academic and scientific world specifically in the areas of stochastic optimization, financial modelling, credit risk modelling and static and dynamic portfolio selection. He has published with Cambridge University press, North-Holland, Elsevier and several international Journals.
18 - Conclusions